{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "-ZF4GR4A_L1c"
      },
      "source": [
        "This example was done using [Colab](https://colab.research.google.com/\n",
        "). You can read and use the Python code in other environments if you have never used Colab before. For example, we used a path to a file in gs://, but you can also just copy that file to your environment and use a local path instead.\n",
        "\n",
        "This example is for **advanced** users who want to understand the data representation. **You do NOT need to understand this in order to use DeepVariant.**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "hbneXvSWAL8i"
      },
      "source": [
        "\u003ctable class=\"tfo-notebook-buttons\" align=\"left\"\u003e\n",
        "  \u003ctd\u003e\n",
        "    \u003ca target=\"_blank\" href=\"https://colab.research.google.com/github/google/deepvariant/blob/master/docs/visualizing_examples.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /\u003eRun in Google Colab\u003c/a\u003e\n",
        "  \u003c/td\u003e\n",
        "  \u003ctd\u003e\n",
        "    \u003ca target=\"_blank\" href=\"https://github.com/google/deepvariant/blob/master/docs/visualizing_examples.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView source on GitHub\u003c/a\u003e\n",
        "  \u003c/td\u003e\n",
        "\u003c/table\u003e"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "Y_244uZxATOZ"
      },
      "outputs": [],
      "source": [
        "!pip install -q \"tensorflow==1.13.1\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "MJ0NcB4f_L1d"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import os\n",
        "import seaborn as sns\n",
        "import tensorflow as tf\n",
        "from tensorflow.core.example import example_pb2\n",
        "\n",
        "tf.enable_eager_execution()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "LRuOxh7N_L1h"
      },
      "outputs": [],
      "source": [
        "def get_bytes_list(example, key):\n",
        "    \"\"\"Returns the bytes-list corresponding to a key in a tf.Example.\"\"\"\n",
        "    return example.features.feature[key].bytes_list.value\n",
        "\n",
        "\n",
        "def get_label(example):\n",
        "    \"\"\"Returns the label(class) of the example. Expected values are 0 (HOM-REF), 1(HET), 2(HOM-ALT)\"\"\"\n",
        "    return example['label'].numpy()\n",
        "\n",
        "def imshows(images, labels=None, n=None, scale=10, axis='off', **kwargs):\n",
        "    \"\"\"Plots a list of images in a row.\n",
        "\n",
        "    Args:\n",
        "        images: List of image arrays.\n",
        "        labels: List of str or None. Image titles.\n",
        "        n: int or None. How many images in the list to display. If this is None,\n",
        "          display all of them.\n",
        "        scale: int. How big each image is.\n",
        "        axis: str. How to plot each image.\n",
        "        **kwargs: Keyword arguments for Axes.imshow.\n",
        "    Returns:\n",
        "        None.\n",
        "    \"\"\"\n",
        "    n = len(images) if (n is None) else n\n",
        "    with sns.axes_style('white'):\n",
        "        _, axs = plt.subplots(1, n, figsize=(n * scale, scale))\n",
        "        for i in range(n):\n",
        "            axs[i].imshow(images[i], **kwargs)\n",
        "            axs[i].axis(axis)\n",
        "            if labels:\n",
        "                axs[i].set_title(labels[i])\n",
        "        plt.show()\n",
        "\n",
        "def visualize_example(example):\n",
        "    image = example['image/encoded'].numpy()\n",
        "    # Read in the image bytestring and its shape: [100, 221, 6].\n",
        "    shape = (100, 221, 6)\n",
        "    # Parse the bytestring and reshape to an image.\n",
        "    image = np.frombuffer(image, np.uint8).reshape(shape)\n",
        "    # Split the tensor by its channels dimension and plot.\n",
        "    channels = [image[:, :, i] for i in range(shape[-1])]\n",
        "    # Prepend an image: RGBA image reconstructed from the 6-channels\n",
        "    channels.insert(0, channels_to_rgb(channels))\n",
        "    titles = [\"reconstructed RGBA (label=%s)\" % get_label(example),\n",
        "              \"read base\", \"base quality\", \"mapping quality\", \"strand\",\n",
        "              \"supports variant\", \"supports reference\"]\n",
        "    imshows(channels, titles, axis=\"image\", scale=5)\n",
        "\n",
        "def channels_to_rgb(channels):\n",
        "    # Reconstruct the original channels\n",
        "    base = channels[0]\n",
        "    qual = np.minimum(channels[1], channels[2])\n",
        "    strand = channels[3]\n",
        "    alpha = np.multiply(\n",
        "        channels[4] / 254.0,\n",
        "        channels[5] / 254.0)\n",
        "    return np.multiply(\n",
        "        np.stack([base, qual, strand]),\n",
        "        alpha).astype(np.uint8).transpose([1, 2, 0])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "AS8XlRzD_L1k"
      },
      "source": [
        "# Visualize examples\n",
        "\n",
        "The following cell reads tf.train.Example protos from a source. This source is in gzipped TFRecord format. We show a few examples, including:\n",
        "\n",
        "Visualize the 6-tensor that represent 6 different features.\n",
        "Reconstruct the RGBA image representation and render it as one image defined in the supplementary materials [here](https://doi.org/10.1101/092890).\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "PYEQP7B-Ae2t"
      },
      "outputs": [],
      "source": [
        "!gsutil -q cp gs://deepvariant/datalab-testdata/make_examples_datalab.tfrecord.gz /tmp/make_examples_colab.tfrecord.gz"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "khdC0_YuqEiD"
      },
      "source": [
        "## For parsing the examples:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "SC4d3WQ_qDud"
      },
      "outputs": [],
      "source": [
        "example_description = {\n",
        "    'label': tf.io.FixedLenFeature([], tf.int64),\n",
        "    'image/encoded': tf.io.FixedLenFeature([], tf.string),\n",
        "    'variant/encoded': tf.io.FixedLenFeature([], tf.string),\n",
        "}\n",
        "\n",
        "def _parse_example_function(example_proto):\n",
        "  # Parse the input tf.Example proto using the dictionary above.\n",
        "  return tf.io.parse_single_example(example_proto, example_description)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "FKXtFYkW_L1l"
      },
      "outputs": [],
      "source": [
        "# This tfrecord comes from HG002 PFDA data. I ran make_examples in training mode so we also have the labels.\n",
        "\n",
        "src = ['/tmp/make_examples_colab.tfrecord.gz']\n",
        "examples = tf.data.TFRecordDataset(src, compression_type=\"GZIP\")\n",
        "parsed_examples = examples.map(_parse_example_function)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 807
        },
        "colab_type": "code",
        "id": "fI_Q0RBN_L1n",
        "outputId": "cdeb7a41-494a-4aa5-e715-a8879ff8e81b"
      },
      "outputs": [
        {
          "data": {
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MBwqdO++8kzvuuIPLL78ch8PB1VdfzYMPPljpS8g9e/Zk0qRJTJgwgYkTJzJg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\ntFfe3FggV/XxGsXVywHmZea6PfWuIK/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5eyPUNRIm/czC/LdFwqQLdY2EST/zMBsgxSje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\nuSTY7XXhcDjrdmOtm2529XxPT8+MtpVtdAA/Mz94f3+/Vq9eXbRD1BJ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            "text/plain": [
              "\u003cFigure size 2520x360 with 7 Axes\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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TTz/Rvn17AO677z6tb5PJxM8//8zWrVu1aPTWrVuzceNGYmNjadiwIQDDhw8v8zsvCEL1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\nvO8xN2LBLfGutQkTJnTDSOAWKsnRnagk752oJJcuueSSmFZyF3obpqX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            "text/plain": [
              "\u003cFigure size 2520x360 with 7 Axes\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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cqAdQGLnnnnu46667uOqqq3A4HFx33XU8/PDDlT6E3KlTJ8aOHcvo0aMZM2YM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\n3t5et9/Z4OCgBgcHFQqF1NLS4n4vJRPHoVBIV199tX74wx+6CeNgMKj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            "text/plain": [
              "\u003cFigure size 2520x360 with 7 Axes\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
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i7rrrLp5++ulKH0Lu1KkTo0ePZuTIkYwaNYobbrjhci5LEIRLwJs9mDBhQqXX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\nYII=\n",
            "text/plain": [
              "\u003cFigure size 2520x360 with 7 Axes\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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HlnuPAErE0n/9619069YNo9Go/f8HJRXdwIEDGTlyJNOnTycwMJD27dszbtw4\nRo4cSVRUFPn5+W69LvX3FO7kc0VkZKRDPnCj0cjjjz/OoEGDGDRoEI0bN6ZXr16MHz++XCPTsGHD\n2LdvH5GRkcydO5epU6eya9culi9fXu5a9urVizfffJPXXnut3HqCcKNzI+kVPRMnTiQ/P1+z0dls\nNlq1anXN9QwGA2+99RYrVqwgKiqKUaNG0blz5yva2R555BGCg4Pp0aMHo0eP5tlnnyUsLOxP26gE\nBUOJuzjSgnAdUVBQQI8ePVi9erVbT/OaxLBhw3j88cfLhHUXBEEQBKHm0rt3b1555ZVKT3syY8YM\nWrZsyciRIyt1HEEQro2FCxeSmpqqvVijJyIigtdff/2qvb9dUVJSohm+O3XqxPLly2ndunW5bUQ/\nCYIgCIJwrUydOpXGjRvzz3/+s0xZq1at2LFjBw0aNKgGyQRBuF4RvSLUFMQTXLgh8Pf3Z8yYMVpI\n9prM/v37MZvN4mUqCIIgCEIZzp49y/fff8+AAQOqWxRBEKqB//znPyxduhSAXbt2UVJSQpMmTapX\nKDuinwRBEARBEARBEITrCTGCCzcM//jHPzhx4gS7d++ublHcYjabmTVrFq+//vpV51wXBEEQBOGv\nwYIFC3j00Ud54YUXqFOnTnWLIwhCNTBhwgS2bt1KZGQkr776Kq+//jp+fn7VLZboJ0EQBEEQBEEQ\nBOG645rDoc+ePZvDhw9jMBiYNm0a7du3r2jZBEEQHBC9IwhCVSN6RxCEqkb0jiAIVYnoHEEQqhrR\nO4IgVDWidwThr4vXtTTau3cvv/76KytXruTMmTNMmzaNlStXVrRsgiAIGqJ3BEGoakTvCIJQ1Yje\nEQShKhGdIwhCVSN6RxCEqkb0jiD8tbkmI/iuXbvo1asXAM2bNyc3N5eLFy9Su3btMnUtFgtHjx4l\nJCQET0/PPyetIAhVhtVqJSMjg7Zt29aIEIyidwThxqam6RwQvSMINzqidwRBqGpqmt75IzoHRO8I\nwvXI9ax3ROcIwvWJ6B1BEKqSK+mcazKCZ2Zmcuutt2r7JpOJjIwMl4rj6NGjjBw58lqGEQShBrBi\nxQruvPPO6hZD9I4g/EWoKToHRO8Iwl8F0TuCIFQ1NUXv/BGdA6J3BOF65nrUO6JzBOH6RvSOIAhV\niTudc01GcGfKSyseEhICQEZhKuYSK3WBAntZoX1b3/45R7efgyNq3br2ra/9WIFTP2lOW32/zmPV\n1fWj36pt9eP62tv469oW2Ped56PW99f1q5c5x/7ZeW76tnVdyKXWU8d1bqPvR12X+pQdX/9ZL4cz\n+rWE0vXSl+vXUJ2XukZqG1dFnjg3AAAgAElEQVTy6es649xWf67SdDL4u6ivX9tCXR9XGjcHx7VS\n0cud4+K4c1+u+tfLo5+PvjxH18b5POmvO33frtYbp3m4qqOeU1dro29vMHhi9G2gfYdrGlejd/79\n73/Ts2dPpk+fzuDBgwHo2LEjAO3bt2fAgAG88sor2v6yZcsc+lHrTp8+HYD169czYMAABg8e7NBP\nYmKiw1bfr/NY06dP1/rRb9W2AAMGDNDGW7ZsGevWrdPaDh48mHXr1pWZD0BCQgLr1q3T+tXL/Mor\nr5CQkFBmbvq2Y8eOLSOX2o86rh59uVqnY8eO2nyd6+j7dYd+LdW119dPTEx0WEN1XuoauTpfKvq6\nzji31Z+rxMREbe3Utvr6+rXt2LGj1seVxn3llVcc1srVuuqvo4SEBDp27FimL1f9q2um70cvl/7a\nch7T+brT9+1qvQGHebiqo55TV2ujlkdFRXHy5Mkaq3Pg6vTOb7/9RnFxcVWJJAjCn8DLy4vGjRuL\n3hEEocqo6XqnPJ0DpXpnxowZBAcHV4VIgiD8SS5cuMCMGTOuS72jytytWzcCAgKqSiRBEP4kZrOZ\nHTt2XNd6Z/78+TVWfkEQHMnIyGDSpEluv7PXZAQPDQ0lMzNT209PT3c7gBo2wlpipbjEig2w2svU\nRzUlgM1p34ojapnNqY3VqV2x01bfr/NYNt2+fqu2dR7P6tTWqtvqZQRlYfX9Oo+tX3jnR1ZebuRS\n+7HqPjvPC12dYlyPr/9c3k9c/Vrior7zGqrzsuH+fOnbelF2HmqZvq1+HP3a2VzU15cXU7Z/d+M6\nr5WK/pjz+XXVl6tjzteSs1z6a8t5TOfrTt+3q/V2JbNzHXUdXa2Bvr2Hfb+mhH65Fr1Tt25dwsLC\n8PX1xWQyARAWFgZAcXExvr6+DvtqHRW1zNfX16GNyWRyaBcWFuaw1ffrPJavr6+2r9+qbZ3HM5lM\nDm3Vfef5ACQlJTn06zx2UlJSmbnp27qSS+1HHVePvlyto18D5zr6ft2hX0t1LfT1nddQnZd+zV2N\nrbZV67oaV99WP45+7fTl6r6+XG3n3LercZ3XytW6Op9fV325OuZ8LTnLpb+2nMd0vu70fbtab1cy\nO9dR19HVGqjlPj4+QM3ROXBteqe4uFiMUYJwnSF6RxCEqqam6J0/onOgVO7g4GBCQ0MrXT5BECqO\n61HvqDIHBARQq1atKpFPEISK43rWOyEhITRo0KBK5BMEoWJwp3M8XB69Avfeey/x8fEAHDt2jNDQ\nULfhsgRBECoC0TuCIFQ1oncEQahqRO8IglCViM4RBKGqEb0jCEJVI3pHEP7aXJMn+B133MGtt97K\nsGHDMBgMvPTSSxUtlyAIggOidwRBqGpE7wiCUNWI3hEEoSoRnSMIQlUjekcQhKpG9I4g/LW55pzg\n//3vfytSDiUGs+EK5ZRTRx+/WX/MVR+uxnPV3lU9V3IWAc6e9h72eq7q68fSl1t1xw0uyu0xwV/3\nbMqMgtKwxvja23ra26uxr7117fV96GW0uRi/EPCxH3e1Jjr5M85bHIou2f9UMlw0d1fXmQw3ny85\nbZ3rXGl8d+MmlyOLqz7c9XWleZUn1x8dz9VYzvNwrqOWuzs3armXlxeBzcoRqhqocL0jXDV9+/Zl\n+PDh1S0GAJ999hmfffaZth8TE0NMTIxDuX6rx7muq75djaO2cW7rXP5Hx3WVh8hVe2cZnPtytwbu\n+nWWu7wy575dje88D+c6arm7uZWUlHDu3Dl69uzpsrw6qWi9ExgYSG5ubrnlgNs69evXL1OmtlEx\nGo0UFhYCEBQUhNls1spMJhNZWVll+g0ICHCo57wP0L17d06dOoW/vz8FBQUAZGdnYzabXdbXj6Uv\nb9GiBefPnwfQjunLTSYTJpOJDz/8kPfffx+AoqIitm3bRtOmTUlKSiIrKwuTyUT79u3Zu3cvfn5+\nWCwWhz5U1LoWi3LP0rx5c1JSUujZsycHDx4kKyvL5Zro5T958mSZcuH656+id4TrkyvlZhauT2qi\n3hGdI6jcdttt1S2CUAmcO3euukUog+gdAeDVV1+tbhGESuLcuXPExsZWtxgOiN6pPho3bsxvv/1W\n3WIA0KhRo+oWQagEDIbyDMt/wgj+hyk20WncZE6+P6+sUbgER2Ov3nisJoP21NVFV2ZFMfYCFMP4\nJ55m/eJ5Sn01obJ+PFfroRp71TFLXNRXx/KkNNGyKpevru3VBJj3BC7r5NYfdzZ62yidu337jDWf\nAP96Dse0vkrsMqiJoJ3PsCqf2q/eeO9pH9ubUkO3q+TW6vESCKkPfkByWs27qRYEgB9//LHSx3jy\nyScrfYzqZuPGjXz66afVLQYAI0aM4PPPP5eHw0KNpE2bNnh4KP9snY3CAQEBmrFWLVeNv6rh9/Tp\n0wA0adJEq2MymWjatCkJCQkAWl6qoKAgUlJSCAgIoHnz5pphGnBp1DWbzWRlZWljBgQEOJQB2lhJ\nSUm0adOG48eP4+fnx9mzZ1m/fj2+vr4UFhaWMcSrc3Lm7rvvZs+ePQ7HTp06pb0M4OfnR2BgICaT\nibNnzwKQnJyMxWLh7rvv1tqkp6djsVjYs2cPfn5++Pr6kp6ezokTJwgNDeXw4cNaXT8/P9LT0wHl\nBQHnH1tnz56lsLCQw4cPa3LoXyTw9fXF19dXM56bTCbtpY5Nmza5nKcgCEJFo/6Ql/sdoSbSt29f\niouLq1sMoZIQvSMIQlXw/PPPA2IMF2ouVWG8rUkG4sqiJs0vOVlx/xNj+F+La8oJLgiCIAiCIAiC\nIAiCIAiCIAiCIAiCIAg1karzBDfA7iXzMLnzxHbnge1spnf26tZ5JQO8t2QeYXqP8j8yw/K85j10\nsrgKfe4unLo7nL3AXcmgH1OP8/ju2ruqZ7iKMj16b3Bn2Uog43fxABdqNvfee2+lezAvXryYzz//\nvFLHEEpxDocuCDUJdx7RoHhbu/PAdg7Jrfcit1gspKamYjKZ8Pf3x9/fn9OnT+Pn56fVPXLkyFXL\n6Oyhrkcvh+qZraJ6TF+tFzhQxgtc35fa1mKxkJaWVqaOu7eF1TbOfbkqdxVWXvVAdz6meoMXFhZq\n4eTV/g4dOuRSFkEQhMpCPDEFQahqRO8IglCViAe4UNOpCg/mmuQl/VdAPMD/mlShETyLTiMac/Kz\nJEgH9Okrfe1bfU5sNfR4oW7fCyX/NvbPHii5q1UsML5TU9Z/l6QYmS8DZkoNvj44Gp/VsORqGPLL\nuDYOq6HLLwJ17J8LKA0nXmDv20snrxelMngoslEI1KY03HghimFZnb++rbq1AP66flSZ1Tqqgdpq\n3xbZ/9S18bV/LkCJW55jr6cat31xCCeP+kxZXVeDvZ06Rp6uvT+E1PPD7xIkF7h/AC4I1YmEQ7/x\nkHDoQk0mPz+f22+/nQMHDrBv3z5eeOEFrSwuLg6A8PBwsrOzKSws5NZbb+XYsWMMGDAAgIYNG3L8\n+HH+/ve/A/DLL7+QmZnJTz/9pPUzYMAAevfuDcDhw4fp0KEDw4cP58KFCwDs2LGD48ePa/XPnz9P\n+/btSUpKok6dOrRp04aMjAyKiorQc9ddd3H48GGeeOIJ3nzzTX7++Wf69etHRkYGKSkpDBs2jJ07\nd3LixAkiIyMBOHr0KD///DO33HILeXl5xMTE0KlTJ95//30SExMJDg6mR48eFBYWEh8fD+DQFiAp\nKYn+/fvz5Zdfav2cO3eOW265haSkJACCg4O1tQPo2rUrLVu2pKCggISEBLZv386FCxcYOnQo69ev\nZ/78+QDk5eVhNBrZvXs3+/btA6Bt27b06NGDy5cvc+rUKa2eGuo8JCSEZ555Rju+YcMGxo0bx2OP\nPeYQol0QBKEykXDoQk1m48aNhIaGVrcYQgWjvvQnucEFQagKJBy6UNORcOg3HhIO/a9JlRnBfY3e\n7N14jsYh3tjqK8fUR6/1UGyrqn22XgGY/Smt5AlF9hzgRruR3GiDPAPYLtvLgHpesCT5HG2beJNq\nVfbzgBxdXut6VvuxEjACxiLI8wBjCeR5gbEYUr0VmbDLhQGMZjDfpLTJKVHksBUp7Wx1AW+7HHZZ\n/ErAaLD3C1Ci9JHnAzk+4KfzHC9Sn2vYDf9+QD0D5JUo8qhy5dnzhdsKwag3/nuB0aLUU3N623Kh\nyB/qFUOev30OhZBX175+BcpxYzGKwds557oHpNrPTap9/YweYGyAZkBP9YCU5Z25+5Fd+JR481sJ\nXD6e7+YKEITqQTzBbzzUtR4xYgSLFy92yOUrCNVNnTp1OH/+PLm5uTRu3NhlHdXr+e677yY2NhaA\n9evXk5ubS2FhIYGBgaxcuRJQclpbLBaaNGmieXD/73//0zyX1brTpk1z+C4YjUYAzevcx8eH3Nxc\n8vPz2bdvH+Hh4Zw5c8ZBrlWrVtG9e3eioqIAJbf222+/Tbt27fDx8WHp0qUkJSVhsVi0/ORqfvHz\n588DkJiYSJcuXUhKSuLIkSOYTCa+++47B1lSU1PJzs4GSvOif/nll1of/v7+OHPhwgVSUlK0z3v2\n7OH06dOMHDlSM7afOXOGl156iY4dO/LUU08B0L59e6381KlTZGdns3HjRhYsWAA45k43mUzasW3b\ntmk5wbOysggPD2f06NFaXvfdu3e7PLeCIAgVjRjDBUGoasQYLtQ0Fi1aRHFxcXWLIVQSs2fPBuRe\nR6h5iCf4jYf60oEYw/9aVJ0n+DkgCMWyqobVrm3f5gPBTlJdojTE+CV7G08Uz27g5aDOTLi0i4+8\nOzM4dRfUArLt7cOA80ADFCO6+j+0GMUD/RKKB3Su076PvV0IkGFvE2Rvl2//rHqnq57qXvCRT2fG\nnNullKse2XkoFnP9FhSrskUnU6a9Xyj1tPayr4fdoM0leLlOZyac3KWMqY6tpwTFS90KXISPburM\n4Au7FO91dZ1rUXrGVW929c2DAOXv5dqdeeH0rtLzEECpV7hZ6Rvs4/sDu+zrZzfofzOmDxM+38WC\nmzoDMCF9F1jtS1BbWeczv4uhXLg+GT58OACffvop9957b7XK8umnnzJq1KhKHUOd79VyresyfPjw\nP/USwYgRI1we//zzz7U5SPh0oar46KOPWLNmDW+99ZYWUnvbtm0AxMTEsGjRIq1uSkoK3bt31wyt\nLVu2pKioiPz8fM0TfMyYMbz44ovMnj2b5ORkdu3axZAhQwCYOnUqc+bM4dVXX6VZs2b4+iqhZcLC\nwli5ciVdu3bl+PHjPPTQQ6xcuZKHHnqIw4cPU6dOHebMmcPChQv597//DcDatWsJCwujU6dOrF27\nloyMDDp06IDRaCQvL4/z588zcuRICgoKWLt2LUFBys1Ljx492L59u8MW4P3336d169b4+Cg3EU88\n8QRr164FICgoiB49epCXl8eSJUsoLCzk/Pnz9OrVi//+97/4+/trHtx5eXno8fb2Zvfu3RiNRjp2\n7AhAQkICHTt21Azz27ZtIyMjQ1vj9u3ba7ogISGBn376SfM6AMXbOyEhgZMnTwKKl7nad15eHqdO\nnWLnzp1kZmaSn6/cw3z77bdaHbWe+uJBQkICJ06c4J///OcfuXQEQRDKRTWGl4c8PBYEoSK5mnQw\nYigXBKGikHsd4UZGNb7WBM/vmujhfq0y/dm5GAwG7byA65cSxFB+/VN1RvDQRmDwUAzTVkrDj0Op\nAdwbxeCshj7X58NW7aZ2J6cXitLA1owxhWng20wpD0QxBFuAm+z1a1FquLXay+ze0AQ4bQGa2bd1\ndMdKUIzXxSiG6Tr2z17KdszFNGjYTDFgqy7k9ezj1bO3CbX3o87b196+HqUu8QYUg7gfpSHY7bK8\nQBrc0qxUHr1hX/UAt3vLcxnG+KRBcLNSo7xqOFfvJ0rs+/qXD7CPc3MzxUDuZZdTDdMebO/Hh9Iw\n7P2+hPe7aUb5MfvTqNuyGXz2pXJgWDelbial4d85jCBcj6hG1co2Pl8NVSGD3oh8NVyrTH/Wi37U\nqFGV7u0vCFfLG2+8gcFgYPLkyQQFBeHv70/Dhg0BNAP4mTNnCAsLw2Qycf78eQoKCrT2gwYNAtA8\nwXfs2MEtt9zCnDlz6NKlC7169SIuLo74+Hhat27Niy++CMAPP/xAz549AcULvHXr1nz88ccA7Ny5\n02ELaN7eGzdu1I6pebLDw8MpKCggNjaW8PBwUlJStDDkO3fuZMCAAcydOxeAuXPnEhQUxNy5czGb\nzUydOhVfX18CAgJo3rw5+/fvJz09nTlz5tCqVStA8f5esmQJBw8epEmTJlru8dzcXObNm6fJ4evr\nq31u0KABqampWCwWzVu+SZMmnDhxwiGft5qzXH0BwdfXl9zcXC08usonn3yCn58f9957LykpKVpY\neYD58+cTGBjIb7/9po2v/uhRjfJqeHrVexwUD/ZnnnmG5s2bO+QUFwRBEIQbjb59+4pXpgCIQUoQ\nBEEQrgbVuFrdBvCqkuGPjnGtMv3ZudSE8yFUPlVmBC8syOHvT07m5KJ5StrpErDZjdyZhYpt2ma/\nd860gcWDUkMvYPMEPCDP7gleVAIWK1hKwOYF1FHajYt5mvVfzsNmU+yulsLSfvG2952r2GXzUOzP\nFnVbomxtBqUtlKbILgIsNiV0ug0lNLnFoPRhMQBmuxx2z2pLiRKuvchejxIlXLoFpb3lIpoh2ab+\ndvQFDEpZpl4uD10/9uOOflFQZAWLzjtcHSdTPz6lfaj9FeECe252W4myXjb7VaKul3ZOSiC8W1v8\ndOOpaxT7/TKlTf4FMECRH1jsucVDwhuSVQJ+VgiwXwMZv59zJYkg/GkkJ/iNx7V4jquh03/88UfN\nYC7e4UJloOa5DggIIDs7m4KCAk6fPu1QJyAggPPnz2ve1CqJiYkkJiY6hOgOCAjA398fHx8fZsyY\nASie1A0aNCA2Ntahrhou3GQylRnTeXxAC6+uot9X+7VYLJjNZrKysjhy5AiA5nGt9pWSkqL1GRQU\nhNlsxmw2c+TIEYKCgmjWrBn+/v40b94cgPj4eI4fP46fnx+pqamaobmwsBBfX1/NgJybm0tubi5Q\nGkJefcvXYrFox9T2al1VbkDzjteXqW0CAwPZtm0bfn5+tGrVij179mjlan2LxUJgYKCWO1xPbm6u\nFkJLlXvs2LEOdYxGIy1atNBCvV+NR5UgCMK14sqDSgxUgiBUJqJ3hKrgqaeeolatWtUthlAD0Ef0\nUpGc4kJlURM9poU/x7WstfrcR494h19fVJ0nuEcW5C4BW6Yyqg3FixkcPaO1+rptka6+Wkf1VL6E\nEu5bNQD7LgHPTEcvcrWs0N6X3mvabB9bHUvt34ojXihGedUD2mb/s9r79KE0bLhKForXeAmKV7dB\n168FxUsdSj2+L9rHUeuqXuP2FwA0L259iPfL9s/F9nbedjlyUDzc1bDnvvZ+1HaXUMKZq/PSHy+y\nl4Hila6X2VO370NpqHg/exur/dg7S5Q6aZnKOtm95jWLeS37Z5syr5BQPzLS1VcOBEEQKp8RI0aI\nIVyocDIzM+nUqRMFBQUcP36cBg0a0K5dOwBat27Ntm3bOHHihFY/NTUVUIy80dHRBAYGanmsAR56\n6CF++eUXHn30URYsWEB6ejqgGGDPnj2rGYL1DBkyhHvuuYfCwkKKiooIDg7m4YcfJjY2Fh8fHzIz\nM7V84KGhoQ5tT5w4gb+/v+bhHB4eTnBwMOHh4XTt2pWdO3dqOb5B8X7+8MMPefPNN/H19eXEiRNa\naHdQQsAvWbKEgoIC9u3bB8C0adM4evQoCQkJFBQUYDKZuOWWW0hJSSE1NVXzjO/SpQt16iihedTQ\n7A0bNuTnn39m3759HDx4kLfffpuPPvqIEydOMHToULZv386pU6c0+R9//HHWrVtHYmKiw7wef/xx\n2rZty4YNGwAlhLpqpO/Zs6eD9/uhQ4do3rw548ePJyEhgS+++IKQkBDatm2rhUQ3Go34+/uTlpZG\n/fr1tRDtK1asYNu2bYSFhZGVlcX999/PmjVrrvp6EgRB+LMYDAYxSAkVzsaNG8vcQwiCyqFDhyRM\nuiAIVcbzzz8vhnBBEKqU5ORkMYRfR1SdEdwANKfUUKw3OPs61XWWytm4DKWGYz8cDd7NdfsllBq7\n1X5Vg7gaHlw/tv7ZgHPObWc8KDXu+rupE6L7rOY3V/t1DvcOpbm79fLo5VON4GbdmAH2ftSom2rI\n87qlYxXf0xSvvUmlYdNBMc47jw9KSHmbmzJVPn25GjLd4NRmjH37LqVGdrU8UFdP7csDQsIUT64s\nG1hTxSAuCNczixcvvi485NV84osXL9bCKQvCnyE/P5/Y2FhtPy0tjcOHXacBcT6ub6evY7FYWLVq\nFbm5uZqHsx41BHj9+vUB2L9/v/Z2a+PGjUlPT2f9+vVafTV3dWFhYbke46B4hJtMJhITE1mxYoXL\nOvfdd5/2Wc1vrnqlO3u2A8yePdth32KxaJ7SUOqRPnbsWFavXg0o4ctTUlKIjo4GICMjg6ysLCZO\nnKjNoX///oSEhJCYmKiNP3PmTJfe8hMmTNBkdUb1eNeXJyYmsmPHDrKysrRjq1atcmgXEBCAn5+f\nyz7VvrKysrj55pu1Y7t37y5TVxAEoaLRe2qKQVwQhKpAH/1GDOKCIFQ2eg9xMYgLwvXN9eIdr/cQ\nF4N4zabKjOC+db3Z+945Gpu8lfDfnkp4cIB6nkqobXskceqh2Hn1FAFYwWjfN6KEG7d5KKHA8VTa\nLVlyjrYh3qTa+9H3q/adZ4Uce1/GEsjztm8BoxVSPaGeXbY8AA+lrtneJscARpsyttFmt7FfhiJd\nCHc/u4zGYsjzsctugzwb5Hgp5apRWAsxXgj4KGX1iiHPC4xFkOcJRk8lBDuALQ+Mqhe53ZvbiBKG\nXDUq23KhyB/qeYDPuXMQ5q3U0a9fERj1hnH7Gque+qko7VPVNpfBWIBiDPeGVBukzO/M3ZN2kWeA\nHHuIc6MXRN+vfPHjVpzT1i8vD8Vg7g05l8HPAkbVyO+FdjXmXAaPm71pfAmoBb95Q2PAmAVH7XOl\nNtS1Kef9zM9qwnhBKMu9995b6fmiFy9e/KfzWt9oVKYBvLLWOjc3V5NbNeJ//vnn5OTkaGH1JZS6\ncCV8fX3x8vLC19eX0NBQ8vLyNMO1c0hud7h6ISMtLY3AwECXRnDnkOHO/YSGhuLr60tycjK+vr5a\niG997mwoDSGutlNzbycnJ2vHmjRpQlZWlhb+XCUsLIxjx44Bive4yWTSDM7OdOzYkePHj2vtzp8/\nT5s2bUhNTSU7O1vz1vb29i7TVg0BrxqVo6Oj8ff3Jysrq4xxXaVdu3akpKQ4rF1QUBApKSnaWHrD\ndYsWLbj99ts5ePCgNlbTpk1JSkrCYrFgMpm0fO4qqvHbbDbzwAMP8Msvv5CUlETTpk1p3bq1thYX\nLlzQPjdt2pSYmBi6devGjh07NGP+xIkTtTrbtm3D39+f7OxsCaUuCEKF4Cp0sTvEYC4IQkXwR+5h\nxGAuuGLRokUUFxdfuaIgUPal6/KQex2hPGpi7uy/ApW5JpVlYHcVMt0dYjCveqouJ/jvl/n7+Mac\n/CBJy7Nts//+zvRwygluKM3FraI6c6tGXDWntUVXlmmFcc81Zf3cJC2vt74c7Mesyth5Bnuebl2+\nbjXyeqZdFi2HNqW5uG32fN/qvjYf1fMce25s5zzcViW/tw3H+WnylQCXlPqZJXZ57PnRi2yKnHiA\npRbkXXZsXFRkzwlu9/62FIDtsn0tVWO7VSeLR+l8NY95dWsPGW/zVM6NzT5Gnl0ONQS7zRPCH/0e\nP5suJ7i9Xuwa5Yufl30ZPHRjXy4V22KDPP09rIfjeuTZE7fbPJQXF4oMYCtSzh9FpS8oeAYpHuQm\nH8gylL5gYLkM1gzxKP+rIznBbzyuJSd4RaMaHZ988kkt1zgoL12IR/lfm2HDhnH06FHNqKp6XQOa\nwVnNU11YWFiuURtwMHyrx1u2bKkZtN31obZVy3NzczXDt74v9XrVj6kvS0tLw8/PTzOw5+bmOuTt\nDgwMxNfXl+zsbAoLCzl79ixNmjTRvKn1c1Y/qwZws9msGZJzc3PJzs4mLCwMf39/UlJSmDhxohYa\nXTUKd+/enXPnzjl4sGdlZWn1QDHCq/v6XOYBAQGYzWYtj3n37t3Jz88nKSkJQDOInz59Wjt/LVq0\n0PZNJpOWf1w1eKuox1u0aMG2bdu040lJSRQVFTm8EKD27bxV23/88ceYTCYaNmyIyWTS5qJ6N6jG\nebVtx44dq10nCoJwY1KewVweGguCUBmUZzAXA/lfF8kJLlQWrnKMq4hHuSA5wW88asJal2cwFwN5\n5XBVRvDXX3+dhIQEiouLeeKJJ2jXrh3PPPMMVquVkJAQ3njjDXx8XMUs1+FjAt9xwLzSY+rv5mIc\nvZFLnPbdhed2VTd3HNjmuS5zbldyhTrOqHKoodRd9amiGpXVXN3gfg76Nu6Olxee3UZpHnEVNVx6\niZutfg4Gp623vbzERT31szoXNSS82lZdz3rj7H3Zz0V58rtbT0+nz+r668+ZDSUkvIo+BL4nhNSH\njLRz5Qwu1FQqRO8IQjUgucavTypK53z//fdljqmG8AYNGjgYTlWjrIq78NyhoaFl6upvjJ3L9Pj6\n+mI0GmnSpAlms9lt/k79cVUO1QDsjN4LXDUqt2nThoSEBMDRqKsa/PWfXclaUFCA2WwuY9zWYzKZ\n2Lt3r0N7NUS7KlNAQAD+/v74+ys3QqpBXT+uut27dy/NmzfH39+f8PBwrV5eXh55ecprl2rI+sDA\nQNLT0x1eEHDl2X/q1Kkyx0AxkoeGhl7xB9epU6eoX78+hw8fLvOywQcffKDVMxqN5OXl0aBBA5KS\nkoiJiWHTpk3l9i3UPOReR7iekVzj1ycVpXf69u0rXplCtSB65/pD7neE6xXJNX79InpHuF6RXOOV\nwxWN4Lt37+bUqVOsXEl12V4AACAASURBVLmS7OxsBg8eTOfOnRkxYgTR0dG89dZbrF69Wsur6g5f\nn7rsXbGcxnWCFY/pC1Bkf95az2APUe4JWJXw6Ga7tzEGRUo15LnRbvw0AnmXwGaBokClbr0SWLJ8\nOW3rBJPqoYTyzrsMOapzUCHUq6uEP89BFw7doAuHfglSa0E9q9Ikz1Pp2+gBZps9HLo9vLfNZg+H\nXgT468KaowuHbrCHMVfHsEKODfzsIcexQZF6FgxAsVJWz95ODftutNnDndubGXVjYVPky7PZ+zAo\nXulFlPYD9tDs9rGMBvt89f2ohuXLylql1lLOhRYO3T6OagBPLYaUfTu4+85u5Pkqa+qHElI+etxY\nAOKWLC89X7qhcmzgZ19HzQhuKy3DBkb7/6IcdWwUWfxUeexzV8PdG62lMnBZiRZgNIgR/HqkovQO\nSDj0GxFZa6GiqUid06lTJ06ePKkZYv/9738zc+ZMQAk3Hh4eTnZ2NkFBQWRnZ9OuXTt8fHw0b+EW\nLVqQlZXl4N3dq1cv2rZty5dffom/v7/2Yy01NZWCggLNYH377bcD0LZtWz755JNyDdi9evVi69at\nBAUFAZCdne2Qz9pkMmntTSYT/v7+tGzZkr1797rsLyEhwcHTOigoSAuJ7u/v7xAe3WKxaGHQ1frZ\n2dnaWK5eBFAxm82YTCYsFovWVj2uN86rHuauDO6qYTk8PJywsDCOHDmiGb2h1GtdNXKHhoaSnp5O\no0aNHDzp3RnC9fj5+WGxWDRvfPUYlHrR6w3jfn5+Wj19qHo96ksVRqNR85zXe8IL1wcVqXcEQRCu\nBtE7giBUNRWldyQculBdiBH8+qMi73ckHPqNh3je/zW5km8yd911FwsWLACUh20FBQXs2bOHnj17\nAtCjRw927dpVuVIKgvCXQvSOIAhViegcQRCqGtE7giBUNaJ3BEGoakTvCIJQ1YjeEQTBmSt6gnt6\nemqeNatXr+a+++7jhx9+0LyQgoODycjIuOJA2cnHKS4u5gxQq76f4q1sd/TJ9HTK7Q1YLgK1UcKJ\neyp5obHnhobSXN4WD7CZAQNkFsG4KU1Z/3YSNquuX7VjX8gssOfLtipe3mpucTXnd5EVbPmKDGDP\nP+0BRWlgCVQ8qW3FSluL3bPa4g1ctsuv5gRH8XwustpzddvsebitijyWy/bV9yzNha4yrG5T1icn\nYfGCIm8ld7aawxuU/vL0bXQ5zVUsF8HmDZne9lzcHlBUrMsPrsuBXiYUPUAh2HIh08cxH3uRrq4N\nCK/XAD8f+zoXK2Pl+UHsrM5Km/NKns0iexmeyjm1eSprkWf3fse+hqCUYT8/GOzr7WM/N/bzTi7k\n1bXXt88pz2DPNW4t7ScPCGngp4wBZHmBNVXyhNd0KkrvdO/encDAQD777LNKDRN7I+QEr2xv+Yqk\nJuQEvxL6N0oXL14secJrOBWlcwBmz55Nw4YNAYiJiWHdunUOuaadQ3L379+f2bNn065dOywWCwcO\nHCA3N1cLT15YWMj69evZunUrZ8+epbCwkE6dOnH8+HEsFgtNmjQhPT2d9PR0jh07BkB6errmSa6+\n5erstZydne1Qr2XLlpw9e5YTJ04wdepUTpw4wT333MOvv/5K27ZtOXr0KF9++aXW3tkDunHjxiQn\nJxMYGEhycjKhoaEUFBRw1113cebMGY4cOVLGU3vFihUkJiZy9OhRTpw4QZ06dcjPzyc8PByAM2fO\naF7TUJqzGxSPaT8/P6ZOncq+ffs4ceIEWVlZZGdnO3zf9F7l6lwDAgLw8/OjoKAAo9HIAw88wE8/\n/aTV8/f3L+ONvmzZMi3Xd9u2bcnOzmbbtm2cOXNGkwegffv2Wp7x9u3bc+7cORo2bEh+fj7NmjXj\nxIkTtG7dGoCMjAxCQkLIyMjQyg8ePKjVr1OnDrNmzWLSpEmA4vkPaF7fTZs2BdBymnfq1In27dsD\nkJiYyO7duxFqLhWpd5KSkjS9U14OZ0GoaJyvNwlTXLOpLL1TXg5nQahonK83yRNes6kovaPXOeXl\ncBaEisb5ehPP8JpPRemdm266SdM75eVw/rPcCJ7J19Mcrgc5na83CY/+57mqnOAAW7duZfXq1Xz4\n4Yf06dNHO34tP3QvpSkPIT3rN3RfqbaThDYcc27rP6tWWk/AYs8JbtAdV7FeYd/dcRsQotv3QvGh\nV0N4F1M2V7Vzf2r+cex1fXXl+nzawPLcfEx16rmWzWbvz/nMOY9tdHHMmyuj1ve1y+kuH7t63Nmu\no7avbc8J7jlPqacf250c6pqo61TeMzz/csrU/vXn37P0WK2bStOIZ/wuodJrMhWpd2JiYoCyhhtB\nYdSoUTXesHw9s2nTJu1FA8kXXnOpSJ0DaC/fqPrHFbNnzwbgyJEjgJI3XA13DY45tVXDeEpKCkaj\nEaPR6DLPt/MNcsuWLR3au6sXGhrKfffdp+2rhuWUlBRMJhOtW7cmKyvLbQ7yRo0aERAQoMmflZVF\nfHy8Vq62UX+QxsTEOMxPj8lkonnz5tq6qP05j/3MM8+UOabmJi8Ptf62bdvIyspyG4ZdPT5+/Hgt\nPLmvr69D+HSV3NxcLYc4wJ49e8qVQTXWl/d/aenSpdpn/QsB4JivXOXs2bOAch3pHwqLgaLmUtF6\nR20nxnChOtBfd2IQr7lUtN5R/9+I3hGqG9E7NZeK1DuqEVKM4UJ1oL/uxCBes6lIvaM+O6lMY/j1\nzPVgWL6e0V93YhC/Nq4YDh1g586dvPfeeyxdupQ6deoQEBCgedOkpaWVeahaYdh0W+ffU39EX9l0\nf+4M3yU4GqpdlRcBudDJ42ll36YrA9ce1TiV6ds5Y3CqV2KXVzW0q3hyZUqctu7K9fuXgYtwMdA+\nv+JyZL2qK0eHu35coV+HP0J55+//s/fuwVEdZ/73R9eZEdEMGgkBGsAIgS0wCBGtjY2TBZbsGxvb\nxJcEF3bM7ibr2yYpshVnk9fejeNK2eu1vRu8eV04TuzsL47Bt4AL22BSVoF/NoTLyoAgIIwuGBgh\ndBlpRqC5SBq9f/Tpnp7RiIuNNELqT5U4c/r06e5zztA6Ot/zfZ7PMw5DSknZvDNM2b59e6qHMKh0\ndHSkegiGUU4q5xzpcHa73f3EZd09fSHtyJ/p06cnrZOTk6N+Btq+aNEiXnjhBd5++21ycnLU+BwO\n8QaaPsbEdnShW3duJ9bp6urCZrOpsXg8HtxuN3PmzFH1pMv6XMj+z3U8iesVFRX88Ic/ZMOGDTgc\nDubMmaPc54lIYVwXwM/FxUR98Pv9SQXwRLE7EZvNdt5xFBUVXfA4DKnD3OsYDIahxsw7BoNhqDHz\njsFgGGrMvBPPlClTUj2EQWWkH5/hi3NeJ3hnZydPP/00//M//8PYsSL+9IIFC9iyZQvf+MY3+NOf\n/sRXv/rVz9V572nhwk18h6bgylzU49UsIMMK240wOAM4eyHQI0JhR6xQ2gU2eHH9z5g9AZqAgl4I\nhKBDPidMh4I+EWa7oxecGeCMQCACzjQIOET7TelQYHUYsEJzOzOgqxuc2bA7/DOmZIsw5s6oFb4b\niGSgBmrPBGc6OHuskN+9Vl8O0bc9EyEyZ0JECrO9QBjsPVCQJUJ5O7PEcTozrRDoUYieAqd8rpwF\npInxBXpQIn80AhEHFPSIPukGZ581FsAZtNp3EO/MDkLBmZ9BDjRlQUGGOJfy3DvPWCsOaIqC953r\nmX/bn8U57bGOG7ipcTMA7+f4IROcDRDIAcaIY+4A7NniHNGBcP5b38aOkDg3TuscddjEeXACTWlg\ntwR6pxXDvsP6UjhluyHrO2PtwxmEyzwg2rKfBaf1nXBOzoU+OJ4Fs3vEOak70YkhtQzmvCMFikv5\nlviaNWsG3UV9ww03XFYhyy8WeZ0vhMvdsS5Dpa9Zs4axY8eyYsUK4w5PMYM55wADpmPQHeI+n0+5\neBPxeDwEg0GampqYOnUq+/fvV3/AgZjX5s2bx+HDhwEhrtpsNvx+vwqDPmXKFK6++mqCwaAKkx0K\nhdQfC7Juc3MzAK+88gpz587l2LFj2O121Z6sK/c7ceIEoVCI8ePHEwqFcLlcXH311ezYsUO1V1hY\nSHNzs5p/nU4nFRUVFBQU0NjYCAjBu6ioiLq6OtxuNw6HgzVr1vDyyy8DInx6MBjE5/NRUlJCbm4u\nIEKCV1dXk5+fz+7duykpKSE7O5tIRNyQ6eHBpah++PBhcnNz8Xq9zJgxg5MnTyo3uETmC9u7dy8u\nl4vDhw+Tl5dHe3s7RUVFatw/+clPABFmzev18vbbb3Po0CEqKytViLWjR48SDAZZuXIllZWVeL1e\nNTYZDn3cuHHU19er0OahUAi73Y7H46G4uJjZs2fzzjvvAMTtL0OvyzHX19ezbNkyDh48yMMPP0xN\nTQ0gHAvZ2dl4vV7GjRPhjYxzIbUM9rwz0H2OcWoahopk3zXj0kwtqZp3TDQSw1CR7LtmwqWnlsGc\ndwa6lzX3OoahQkZ10zH3OqlnMOedgVy4X8QhPhQu6pHu1L6Y47ucQrcnI9l3zbjDz895RfBNmzbR\n3t7OD3/4Q1X21FNP8a//+q+8/vrrFBUVcdttt13SQe39tL8ImXVlbnyBbpKx8nYTJhamHOuz/JHr\nEYTjWbqN04FsxJnoQsTJ7kXlpyadWPhz+bzZRnyocfn7rUfbr4tYSHesNqTZJ9saR5pWVx7TGKuf\nDK1ur7W08qOPmXI9NP85th1r3JnWT4d2fjKBoLXsJBYH3GH132WNy6kdt+6W1+8de4k50jutPj7T\n1mX/EeBKqzxotVFg7X/WKh9jjT1ktdOm9eOy2rFrY+lGXF8bSvjHZu0vr4vcx27V77b6ywR8Vp8A\n44FTWn9ZVttfAjKgZGau6tPps4RxnxHGh5JUzDvJblRN6PQYI12ETzV6DvF169YZYXyIScWcI/tN\nJDF0+ieffKI+O51OfD4fc+fOxefzqZDcfr+fYDCo5qxQKERhYSFTp06lq6uLcDhMOBzmL3/5C83N\nzSxevJitW7ficrmYNm0aIIRhmSM8Ly8PEOG2bTYboVAIm82mHMp2u13tt3jxYt5//301xubmZr79\n7W8D8Je//IWrrrpKucMXL14MwI4dO9i8eTPz5s2jvb0dgCNHjpCXl8eRI0fUW9kTJ05kwYIFAHz6\n6aeACDEuReCVK1eqh51tbW1ce+21tLW18fWvf13l+K6uriYYDDJ//ny++c1vsnHjRnJzc/F4PEoM\nhliebRChxKUz3OPxsG/fPmbOnElTUxM333wzLS0tNDY2MnPmTA4ePAgIQbq0tJRf//rXjBs3Tono\nlZWVHD16lLKyMvbt28f3vvc91c9rr71GS0sL1dXVSoAvLi5m2rRpShAPBoMcOnSI2bNnq1zi+fn5\nVFdXU11dTXFxMcXFxXz1q1/F6/Vy3333qdzljzzyCM899xwAFRUVnDp1irlz57Jp0yY6Ozu57rrr\nVJ/33XcfAH/zN3+DYWhI1byT7H7HPCw2DBVGGE8tqZp3komQRhg3DBVGGE8tw+XZjrnXMQwV5l4n\n9aRi3kkmQprQ6TEud+F5uGOE8fNzXhH8rrvu4q677upX/rvf/W5QBjQQ3ZYwniwwZtaMueJI0hAC\nbA8xMVuK4xATw+XvIylYy1DnUsBNI3ZmeomFJO+z2upFCKcyxLpsI5OYeJ1JLBc41pikjt+dsJ+W\nr1q1I0X2iDXu7lids2mnGTtuWmwfeUzyuPKsZQQhFGdb7eVDv5DtMmpn1KrnICY8RxAisqyTofXT\nbdW94g0ILYxZ9PusPv+fN8T6rxbGwrlLwV5Hnmf9HQc5Fj0PfAQhYssQ8TIneA6x6yvHnqH1JcX9\ncdo2gGkJ/YUR11QP825DvTRQMgnUVN0Lzm4IZAqnf9un+zFcWobLvCNdi1KM1EXJ0SaQj/Rw7MOR\nu+++mzVr1qj17du3c8MNN7B9+/Zz5pg2XDzDZc6BgV3jAHfeeSder5dQKMScOXPIz89n27ZtceI4\nxEJ4S/FZ3vzm5OSQl5dHY2OjEqeloCxzjEsX9ty5c3G73dTW1qoyECHRGxsblXgt85PLsONFRUW8\n9957AEybNk2Juzk5OTQ1idgyeXl52Gw2vF6vyud91VVXEQwG1Vjdbjc33nijOgbZTigUUmUvvvgi\nADNnzlR5wHNycli9enW/kO2vvvqqake66KXYP2PGDBYtWqTqtLe3E4lECAaDTJo0id27dwPwta99\njTfffFO1WVVVFZd/3O124/F44vKYS+R53rhxoyqz2WwcP35cOe0BSktL2bx5M3a7HafTqfKKb926\nVV3fXbt2KYe/dHq/9tpruFwunnzySbUNUEI3iJcXpLtf/x22f/9+tm7d2m/MTqeT6dOn09jYSFFR\n0Tm/m4aLZzjNO+d6MGceGhsGm3N9x8xD40vLcJp3ziVCmnnHkErMvHNpGS7zjrnXMaQSc68ztAyX\needcIuRoE8iNAD70nOs7NhoF8vOK4JcNPQihNIgQS7usMjsxp3CP9VNglUlHsQxj3okQffX821cQ\nE8jl2QpaP/L3lHRVS3c0xIcYByG0tiFc17nEBNZuhHMb4sXmPqsPBzGHOsTEcNl+n7V/J1BM/7zn\n3VY76Vp7WP1Lh7h0nmdZ26UQbLfK/Fpb+QltSwd3s9VmKzDFGo887pC2zxnrJ9+qEwUmokLBq+OX\nYdezEdfEafUlI5Ues9o4qbU9AXGe+og50x3aOTlDLOy6vMbpCKt3mtX+WOu45LXQz6V0sctzqDv2\nDQaDwWAYAmR47IqKCrZu3cqiRYsYN24cNTU1yins8XgoKiriqaeeoqysjJMnTxIMBmlvb2fmzJl8\n/etfZ8GCBTidTtXuihUrmDFjBm1tbUqwnTdvHvPmzSM7W7xZJl3VN998sxJfE/N2u1wuli9fzo03\n3sjOnTvZv38/u3btoqSkhHvvvReA119/HYCmpiYcDgfz5s1j7969zJ8/X4m+kyZNAuDkSfGL3uFw\ncO+993Lddddx22234XA4mDBhgup3+vTpzJs3j3A4TEVFhRKnDx06xLx582hpaaG8vJyWlha8Xi+7\nd+9W7u/q6mpOnjzJPffcA8AVV1zB6tWrVdslJSWq7tNPP83+/ft54IEH+M53vqNeOIBY6PU5c+aw\nZMkSFi5cyAsvvMDSpUvJzc3l+9//PiBc2fL4ly1bps7jwoUL2bBhA//8z/+sXoCprKzk+eefjxvP\nL37xC7Zt24bdbmfZsmW0tbWxfft2bDYbLpeLZcuWsXHjRhWKHkRO829961uEw2FWrVrFK6+8wqRJ\nk3jllVcA4r4LX//61wHYs2cPIISKzk4TEcdgMBgMBoPBYDAYDAaDwXB5MSJE8O6j+8malSsEWyvn\ndBxStEx0+epldmJu5kTGJKzL9nqIiegQH/48Edm+J8m23CRlvVZ7cnnG6jcHaCF2jDaEiFxorcvw\n7UGrzzRigvkYYk7wKLHjlQK7RH9BLZ2YICz3S9faLFoOX6qPtS3r5i639q+Pb99NTMjWBXd5LBL9\nGspUwbnEROmJ1lJ3dEt6tWPSRWzpJO9OqCuvr9wnizjnvRqj/j3QzkHJ1bnU/cU8HB5t6E47g2Go\nufvuu0249FHIH//4R8rLy6mrq+ODDz5QzmqJjNiQ6PIFlPt5//79vPbaa0nb37ZtW9y6FKRlvm/Z\n7ubNmwcc47naX79+fb8yl8vF5s2b1fKmm25ix44dhMNhfv7zn9PWJt62+9///V+2b98eJ9Z6vV4W\nLFjAvn376Orqora2FoAPPvggzkEu3duJx6e7xX0+n9pf7pdYVltbq9qWrnEdvf0DBw4o4XrPnj1x\nYrnuHpcvHMj2QZxfeZwPPvggEMtRruN0OlWf+nnZsmULNpst7u1em83Gli1b4sZZW1sb57yXY5T1\nEs/LlVdeqcLSG0YPfX19xiFlSBlpaWnGITUK6evrM+HSDSlj3759Jlz6KMPc6xhSibnXGZ1Mnjx5\n1LnBDcOHEydOjDo3+IgQwQG6D3WyV67Y54K8jvp9TAaxkNjdxEKlj0G4vbOJD5mt7x8lHhkSXOb3\n7iX+bPYgRNJkucP7iBd/E5H1pNO4R1uCEJplmzKPdwQheuuifo92fImkJYxN71vm7s5CuKQnaNvS\nrHalO5s3oG+hKI8Le26FQydJOHR5LmW4+sTjliHipWM7SuxcJvvGSqFbDysfJf4Fhc9D4jU/R3nJ\nLKBHhEzvNuHRRw0ul8vcrBpShswjvmbNGhW63zDy0R8KNzU1qRzTek5rn8+nRM3i4mL8fj+zZs3i\ngw8+YObMmRw+fJi8vDwV0hzoF3ZcEgqFKCkp4cCBA5SWluJ2u2lsbFTbi4qKqK2tVWHNARUa3W63\nx4m/ich6cixdXV34fD7lXl63bp1qc+LEiTgcDmbMmEF1dbVqd9++fRQVFanjSyQUCsWNTe87Ly+P\nRYsW4fV6uf3221m1apXaFgqF8Hg8LFq0iA0bNtDV1aXaGSjseWK5PJe6wJx4fk6dOqUc23l5eRw7\ndoxAIMDp06f7HYv8fy5fRrDb7bhcrrgXFD4Pdrs96R/gyeaV8vJyioqKgHOH7jeMLPR7HfOQ2DDU\n6N85c989etBFSDPvGFKJmXdGB+Zex5BKzL3O6EQXIY0gbhhq9O/caBDER4wIrrM3tB+OEhPF9W3W\nMmtGrhCIZbjtbGKiNvQXTzMQIbYdiLMWJZaHPItYjnC9fgZwGiEW+xAu8KMIx7Hb6ksK8hIZot2H\ncIC3IhzSPqDI6vM4sbzfcgy6m1yGQJdthayyVmKu6narDRsxB7YU2juIhQ13I8KxQ0yMzyQWdvzY\ncgjUi37sCDH+FLDMcoJ/Vh/Lja6PWS5biQnden5wecwuq88g4EWEQG+zzmWX1Wd2QrtnrM9Z1r4h\na98vWe1mEgu9bkNc/y7EdeohFq5divAy5LvsZyzixYJ0xLEdB8Zbx2CH/Bm5jA2hwu87rQgBASvH\n+vFx0H3UOMdHGvJGNdkNqywzznHDYLFp0yb+8Ic/qPV169YBIsQ1GKF8pDJhwgT++Mc/nrPOnXfe\nyaxZs2hoaOBrX/saDQ0NStQGCAQCcfUDgQDLli1j9+7dNDU1qdzd4XCYY8eOcezYMZW/GoSAGggE\neOSRR3jnnXf4x3/8R/7hH/6BPXv2cPDgQX77299y4MABAoEAU6dOVfsdO3aM5uZmvve971FZWclP\nfvITDh48yHe/+11+/OMf4/V6Wbt2rQrX3draSjgcjsupPXXqVK655hoaGxsJh8OUl5fj8Xh48MEH\neeeddwC44447WL9+PYcPH+bgwYOAyPldVFTEvffey5YtW2hubua3v/0tixYtAmDcuHEEAgFaW1vZ\ntWsXdrudkpISysrKiEQi1NTUUFxczL//+78rB3YgEMDhcJCVlaUc79Ll3dLSwsMPP0xeXh5jxoxR\nLx9s3LiR+vp67rvvPl577TU6Ozu59tpreeaZZ3j11Ve55557+PGPf8yCBQs4ePAgDQ0Nce0uWbKE\nlpYWTp48ic/no6ysjGeeeYaqqipqamrwer3Mnj0bgIMHD7JkyRJmzZrF1q1bGT9+PBUVFbz66qt4\nvV48Ho8KBy8F+HXr1rFt2zaCwSBut5uXX36ZZ599FpvNRk1NDXfeeSelpaUq/L4UxUtKSli0aBFP\nP/30eb+fhsuPC3kwZx4eGwaLC/lumYfHI48LuabGOW4YLC7ku2Wc4yMLc69jSCXmXmd0ciEipBHK\nDYPFhXy3LnehfESK4BdEaFosHHg2/R3b0nWtO8HtxJzSIERQfV3/HZRmlRdY6xOsNqdZS3nmE93Q\nMsS6HNs4a6mHar9C66sXIfbK/eS4ZOhvKdw6EtqIN3rFyLL6lIJ+lPhw5rJfKbJPfAOcC2PnzG6N\nb6PlBL91YcyVnfh7PLFt/SWCHmCSdjw9wHTr83iEiJ1Hf6LEwtXLUOYOrW6i0x/EucgYYBvEQq8n\nIwqUnmMMOj1ooeWNW9xgMBgMg09paakKB37gwIF+jm3pStad4NXV1djtdiXw+nw+bDabEr/lPiCc\n1k6nkyeffBKAVatWMWHCBJYsWYLH41GCrdPpjHNDT5gwga6uLjW2xx57DECtgxCw7Xa7Gldtba3a\nT45ry5Yt5OTkxLmy9Tb0XNo6tbW1PPbYY8qt7XA44tqQx3jttddSW1tLKBSirq4Ou92Ox+OhqqqK\nW265Ja5Nt9tNKBTq5zp3u91xodJ1t73H41FRHfx+P4WFhezevZv29nZ+9KMfMXfuXH7zm9/0G7/d\nblfh6u12O6FQiF27dqm6yVJ2PP/88/j9/gHTecioAsmw2+0UFxfHlblcLhWCX2fChAnqRRyDwWAw\nGIaCefPmpXoIhlGMEaQMBoPBYDAYhi+jVgTvPrGfwHg7EYRROJIBoShE0oWG2WrVC2UAYYjYINQN\ngXSIpkEgTdQPZECoD+iDqCZmhxCRxCNY29Mg0guhNLF/SArC3RDN0nbKEttaeyCUbe0DRKIQyhT1\nQ52ibUAJ25EsCGnifCgAUQe0potx0mUdg3Vvro67m1h+b+lwt0KbR4HWDIha+wQQ50cSbQXPwgnY\n00VbUXncabD599eLfbwN0A0Rh9gmw85HM8RxBkA4zx2olwmivaJOwBL2oxkQyIZIxOojQxxjIE0s\npXYe6Lba7RLHEs223NcyZHy6KAtFRHuAegEimgatEWuM2aiXGCIZEDprjcMuD1yMQV7HgBTbQ1b/\n6eJ7QhjIgIj1vyxkhWmPpsO4CXZamkIYRhfGiXtpWLFihRFYPgcmj/jo5IknnmDv3lhsnNraWhWe\nWxdrT5w4wdKlS9m0aRNz587F5/MRCAQIhUK4XC6am5ux2WwqdLbMMQ4oodpmsxEOhyksLCQcDtPc\n3KzE1vnz56v85LfddhtVVVUEAgFmzpzJzp0743JT19TUMG/ePH7xi1+oPh5++GHcbjf79+9X4dL9\nfj9PPvkk7777GA5FPAAAIABJREFULo2NjeTl5XH//fezZcsWcnP1EDmoMPAgXNETJkwgEomoep99\n9hlz5sxR9aV4X11dzeOPP85bb72lyuRSfxlgxYoVXHPNNSofenl5Ofv27VMubbfbzZo1a9i4cSPj\nxok3HEtLS6msrOSb3/wm7e3teL1e9u7dqx7kt7S00NbWxk033RQXgv7aa6/l5MmT3HvvvRw8eFDt\n4/F4qKio4OzZs1RWVrJkyRIqKysB2Lt3Lw6HA5/Px4IFC1SZDJnf0NDAqlWraG9vV/vk5+dz9OhR\ngsEgoVBIha2/+eab1di8Xq9ypFdXVwNC2M/Pz6etrY3rrruOnTt3JvlmGkYyJremIZWY3JqjE5NH\n3JBKTB7x0UdfXx+PPvpoqodhGKU8+uijPPHEE6kehmGIMXnELw3Hjx9P9RAuSy73POKjVgQHaDk9\nsAhZcNVcAALWGXICXVFwpkNHFJw9EM0U61GAPqHvin/Ani32cUqhtw+cveJzR1RsR+4n/0Z3inV7\nmjCQB6witbTE1mi+aFdH1pNEXaLdAiyxGHD2aZ+1dhXS1W6pyk1pUNAHTdmxfVT9KDTlg/etD5l/\n20ICmdZxRcGZCTet/BCA998UTnBnevz4OqLCNO5MR4QeT9hGGJyWm7rDGrsTaEKcHwCn5druSI+N\nrwOwWznFI72xOiCOraM3dm3i+gQKopZ4raGf1w6t3B6FSE//tjqwjks7T/Kz3o4zCs7CWB/HgbFW\n9AFnD+w1ecVHLGvXrlVCZOLScGEYAfzzIx2n69at47333lMh1NetW2ceGI9gzpW7efHixerzgQMH\n4m5qp06dqtzcugt8woQJzJw5E0AJy7q7PC9PhF9xu93KXR0KhZg7V9xbVVVVKQHZ6/XG9enz+Sgt\nLcXr9fL973+/n6tar1tYWMjq1avj2nrssceS5gDfsmWL+izru91uOjs7VbjvxBzfso5sMy8vD6/X\ni9vtVoKy5KWXXmLDhg2qTDq/pevb5/Nx11139Wtbd+rLsUnBWx6DDFkvXyg4cuQIADt27FDO7s2b\nN6s2XC4XLpdLufMT2blzZ9xLDNJRLucHHbvdTmFhYdwfivJlBn1/+SJ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            "text/plain": [
              "\u003cFigure size 2520x360 with 7 Axes\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "# After you run this cell, images should show up.\n",
        "for example in parsed_examples.take(5):\n",
        "    visualize_example(example)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "_hrcCQI4tMgj"
      },
      "source": [
        "# Use Nucleus to parse more fields in the `tensorflow.Example`s"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "6BKlhfOsDBi_"
      },
      "outputs": [],
      "source": [
        "!pip install -qq \"google-nucleus==0.2.2\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Eky9SpOxrQtj"
      },
      "source": [
        "### First, look at all the keys in the `tensorflow.Example`"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "BYynJ6FfrRVr",
        "outputId": "a9dc48d7-df3b-4a3f-f76c-8ce854fdeb9d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "['variant/encoded', 'image/encoded', 'label']\n"
          ]
        }
      ],
      "source": [
        "for example in parsed_examples.take(1):\n",
        "  print(example.keys())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "wfkJsgjdEmBk"
      },
      "source": [
        "### We can use the Variant proto to parse `variant/encoded` field."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 663
        },
        "colab_type": "code",
        "id": "m1JoluVGElU2",
        "outputId": "34195174-1f4c-49ac-8bda-b486c7198c65"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "reference_bases: \"T\"\n",
            "alternate_bases: \"C\"\n",
            "calls {\n",
            "  info {\n",
            "    key: \"AD\"\n",
            "    value {\n",
            "      values {\n",
            "        number_value: 31.0\n",
            "      }\n",
            "      values {\n",
            "        number_value: 24.0\n",
            "      }\n",
            "    }\n",
            "  }\n",
            "  info {\n",
            "    key: \"DP\"\n",
            "    value {\n",
            "      values {\n",
            "        number_value: 55.0\n",
            "      }\n",
            "    }\n",
            "  }\n",
            "  info {\n",
            "    key: \"VAF\"\n",
            "    value {\n",
            "      values {\n",
            "        number_value: 0.436363636364\n",
            "      }\n",
            "    }\n",
            "  }\n",
            "  genotype: -1\n",
            "  genotype: -1\n",
            "  call_set_name: \"training\"\n",
            "}\n",
            "end: 19503713\n",
            "reference_name: \"chr20\"\n",
            "start: 19503712\n",
            "\n"
          ]
        }
      ],
      "source": [
        "from nucleus.protos import variants_pb2\n",
        "for example in parsed_examples.take(1):\n",
        "  variant = variants_pb2.Variant.FromString(example['variant/encoded'].numpy())\n",
        "  print(variant)"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "visualizing_examples.ipynb",
      "provenance": [],
      "version": "0.3.2"
    },
    "kernelspec": {
      "display_name": "Python 2",
      "language": "python",
      "name": "python2"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}
